Run Claude Code against ChatGPT Codex via your Codex CLI OAuth.
Tree of Thought CLI - Multi-AI mode with Claude + Gemini + Codex for Claude Code
Telegram bridge bot to run local Codex/Claude CLIs
Lean output compaction for terminal-heavy agent workflows.
Codex CLI integration for Ruflo (claude-flow) - OpenAI Codex platform adapter
Codex CLI is a coding agent from OpenAI that runs locally on your computer.
Add MCP servers to your favorite coding agents with a single command.
The open agent skills ecosystem
An ACP-compatible coding agent powered by Codex
Next.js development tools MCP server with stdio transport
Local-first code intelligence for AI agents (MCP). Self-contained — bundles its own runtime.
GitLab MCP server for projects, merge requests, issues, pipelines, wiki, releases, and more
Dozens of cute icons made with love by CodeX for your projects.
Multi-agent AI dev team that runs from ~/.minions/ — five autonomous agents share a single engine, dashboard, and knowledge base
Mobile and Web client for Claude Code and Codex
One-command installer for Sellable MCP in Claude Code and Codex
Loads environment variables from .env file
TypeScript loader for cosmiconfig
<p align="center"><code>npm i -g @openai/codex-responses-api-proxy</code> to install <code>codex-responses-api-proxy</code></p>
Generic MCP server for calling x402-protected APIs with automatic payment handling
TypeScript SDK for Codex APIs.
Multi-agent orchestration system for Claude Code - Inspired by oh-my-opencode
Detect if code is running in an AI agent or automated development environment
Native binary for Claude Code on linux-x64
Ralph Wiggum Loop - Iterative AI development with AI agents. An autonomous agentic loop that drives Claude Code, Codex, and OpenCode.
Clean interface to discover configuration file locations forAI coding assistants (Claude Code, OpenCode, Codex). Shows global and project config paths, handles environment variable overrides, and determines which config is effective based on precedence rules.
Ralph Wiggum Loop - Iterative AI development with AI agents. An autonomous agentic loop that drives Claude Code, Codex, and OpenCode.
cangming-ai-dev-kit provides cross-agent development skills (plan-first, safe-code-change, code-review, verify-before-done), domain-specific knowledge (Flutter/Dart, HarmonyOS/ArkTS/ArkUI), and shell scripts. Install with `gem install` and use the CLI to sync skills to Claude Code or Codex.
Extends ace-llm with CLI-based LLM providers like Claude Code, Codex, Gemini CLI, OpenCode, and pi-agent
rails-ai-context turns your running Rails app into the source of truth for AI coding assistants. Instead of guessing from training data or stale file reads, agents query 38 live tools (via MCP server or CLI) to get your actual schema, associations, routes, inherited filters, conventions, and test patterns. Semantic validation catches cross-file errors (wrong columns, missing partials, broken routes) before code runs — so AI writes correct code on the first try. Auto-generates context files for Claude Code, Cursor, GitHub Copilot, OpenCode, and Codex CLI. Works standalone or in-Gemfile.
A Ruby library that provides a unified interface for discovering and accessing skill configuration paths for 49+ AI coding agents including Cursor, Claude Code, Codex, Windsurf, and more. Handles platform-specific path resolution, environment variable support, and automatic detection of installed agents.
Interactive rake tasks to generate context files for AI coding assistants (Claude, Cursor, Windsurf, Codex, llm.txt). Uses RubyLLM to analyze your codebase and create platform-specific context that helps AI understand your project.
Embeds a FOSM-aware MCP server and ACP agent into your Rails development environment, giving coding agents (Claude Code, Codex, Copilot) runtime intelligence: database queries, logs, code evaluation, and deep introspection of FOSM lifecycle definitions, state machines, transitions, guards, and audit trails. Built on the FOSM (Finite Object State Machine) paradigm — declarative lifecycles for business objects where AI agents operate within bounded, auditable state machines.